Staff Profile

Career Summary

Biography

Stephan K. Chalup is an Associate Professor in Computer Science and Software Engineering at the University of Newcastle, Australia. He received his Ph.D. in Computer Science (Machine Learning) from Queensland University of Technology in Brisbane. He spent his undergraduate years in Germany at the University of Konstanz and later completed a Diplom in Mathematics with Biology (~Masters by Research) at the University of Heidelberg. He is the leader of the Newcastle Robotics Laboratory and of the Interdisciplinary Machine Learning Research Group (IMLRG). His research interests include autonomous agents, computer vision, dimensionality reduction, human centered computing, machine learning, and neural information processing systems.

Qualifications

PhD, Queensland University of Technology, 26/10/2001

Diplom in Mathematiker (equiv Degree), University of Heidelberg

Research

Research keywords

Autonomous Robots

Computational Intelligence

Data Mining

Dimensionality Reduction and Kernel Methods

Machine Learning

Medical Image Analysis

Neural Information Processing

Vision and Image Processing

Research expertise

The Interdisciplinary Machine Learning Research Group (IMLRG) and the Newcastle Robotics Laboratory have the common objective to advance research in the area of Anthropocentric Biocybernetic Computing. It investigates the complex interactions between humans and their environment on all levels including the cell-, circuit-, and body-levels and the ecosystem. When applied to real-world computing and autonomous agents the aim is to develop systems that approximate human-like skills on tasks such as vision processing, facial expression analysis, space representation, and human-robot interaction. Machine learning techniques are employed for fine tuning the parameters of general models until they perform at extraordinary levels of skill on selected tasks. Biologically motivated models are complemented by alternative designs. The strategy is to approximate human-level skills in artificial systems from several different directions, that is, through interdisciplinary projects in collaboration with experts from relevant disciplines (e.g. electrical engineering, architecture, neuroscience, and applied mathematics). Associated projects involve computer vision, data mining, machine learning, pattern recognition, time series analysis, and intelligent system design. Our special interest is on applications of kernel machines and more specifically on methods for non-linear dimensionality reduction or manifold learning.

Languages

English

German

Fields of Research

Code

Description

Percentage

080109

Pattern Recognition And Data Mining

40

080101

Adaptive Agents And Intelligent Robotics

30

170203

Knowledge Representation And Machine Learning

30

Memberships

Body relevant to professional practice.

Member - Senior Member of the IEEE

Member - Australian Computer Society (ACS)

Conference Chair

Australasian Conference on Artificial Life and Computational Intelligence (ACALCI 2015)

Editorial Board.

Editor - Algorithms

Editor - Paladyn. Journal of Behavioral Robotics

Editor - Central European Journal of Computer Science

Editor - Open Computer Science

Member - International Journal of Advanced Robotic Systems

Awards

International Competition

2008

RoboCup World ChampionRoboCup Federation (China)First place for the NUManoid robot soccer team in the Standard Platform League

2006

RoboCup World ChampionRoboCup Federation (Germany)First place for the NUbot robot soccer team in the Four Legged League.

Invitations

To See or Not to Be in the Four-Legged LeagueDepartment of Brain and Cognitive Sciences at The Massachusetts Institute of Technology (MIT), Cambridge, MA, USA, United States (Invited Presenter)

Grants and Funding

Summary

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2014 (1 grants)

Applications of Feature Selection Methods for morphological characterization of images and subtypes of brain tumours
$11,611Funding Body: University of Newcastle - Faculty of Engineering & Built Environment

2007 (2 grants)

Shaping social and cultural spaces: the application of computer visualisation and machine learning techniques to the design of architectural and urban spaces$275,829Funding Body: ARC (Australian Research Council)